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Yezdi Antia

dblp:27/10905 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2000
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
1 paper
Physical-layer communications · 61% Network measurement and analytics · 30% Vehicular, aerial and satellite networks · 9%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Network measurement and analytics › anomaly detection
burst detection
0.012000
A sub-burst DFT scheme for CW burst detection in mobile satellite communication · IEEE J. Sel. Areas Commun. 2000
Physical-layer communications › signal processing for communications
discrete fourier transform
0.012000
A sub-burst DFT scheme for CW burst detection in mobile satellite communication · IEEE J. Sel. Areas Commun. 2000
Physical-layer communications
signal processing for communications
0.012000
A sub-burst DFT scheme for CW burst detection in mobile satellite communication · IEEE J. Sel. Areas Commun. 2000
Vehicular, aerial and satellite networks
satellite communication
0.012000
A sub-burst DFT scheme for CW burst detection in mobile satellite communication · IEEE J. Sel. Areas Commun. 2000

Methods — techniques the papers use, named apart from their topics

probability of false alarm and miss detection analysis · 0.0DFT-based detection · 0.0
YearPublicationVenuePosition
2000 A sub-burst DFT scheme for CW burst detection in mobile satellite communication
abstract
This paper presents a new idea to detect a continuous-wave (CW) burst with unknown frequency using the discrete Fourier transform. Given a CW burst of certain length, an obvious detection scheme would be to compute the DFT power over the whole burst and in the given frequency bins that cover the total frequency uncertainty range. This may result in poor performance when the CW frequency is not exactly in one of the DFT bins. The new scheme divides the CW burst into L sub-bursts and computes the summation of the DFT power in each sub-burst. With very little increase on the DFT computation complexity, the overall detection performance can he greatly improved. The analysis employs a unified approach to derive the expressions of probabilities of false alarm and miss detection for both the conventional and the new schemes over the additive white Gaussian noise (AWGN) channel. Simulations are done for both the AWGN channel and the satellite fading channel.
Zhen-Liang Shi, Yezdi Antia, A. Roger Hammons Jr.
IEEE J. Sel. Areas Commun.2